Summary1. Zoonotic disease control presents significant costs and challenges in human and wildlife populations. Although spatial variability and temporal variability in host populations play a significant role influencing the spread and persistence of pathogens, their impact on the effectiveness of disease control are not well understood. 2. Field studies are impractical for many zoonotic diseases; thus, simulation modelling is an alternative. Some research has experimented with metapopulation models of host-pathogen systems, with discrete host populations distributed on a network of connections or on a onedimensional transect of contiguous cells. Little attention has been paid to treating geographic space as a fine-grained two-dimensional continuum, a more appropriate spatial model for many generalist host and vector species. 3. Using raccoon rabies as an example, we apply an individual-based spatially explicit stochastic simulation model to evaluate effectiveness of vaccination barrier strategies to control rabies. Barrier width and immunization levels are varied over landscapes with habitats of varying quality and spatial heterogeneity, resulting in varying degrees of host connectivity. 4. Our results demonstrate that spatial heterogeneity in the landscape does affect vaccination efficacy. The probability that rabies will breach a vaccination barrier is greater and rabies incidence is higher in landscapes with (i) overall good-quality homogeneous habitat and (ii) overall poor-quality habitat with high spatial heterogeneity, than in landscapes with overall good-quality habitat and high spatial heterogeneity. The influence of landscape conditions on disease dynamics decreases with increasing population immunity. 5. Synthesis and applications. Using a spatially explicit stochastic simulation model, we demonstrated that landscape spatial heterogeneity and vaccination control will interact to influence the success of controlling infectious disease outbreaks. Further, under some landscape conditions, insufficient vaccination is counter-productive because immunized individuals (i) reduce the number of disease transmitting contacts, preventing the disease from growing rapidly thus depleting the susceptible population; and (ii) survive to replenish the stock of susceptible animals through reproduction, facilitating disease persistence.

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The complex epidemiology of vector-borne diseases creates significant challenges in the design and delivery of prevention and control strategies, especially in light of rapid social and environmental changes. Spatial models for predicting disease risk based on environmental factors such as climate and landscape have been developed for a number of important vector-borne diseases. The resulting risk maps have proven value for highlighting areas for targeting public health programs. However, these methods generally only offer technical information on the spatial distribution of disease risk itself, which may be incomplete for making decisions in a complex situation. In prioritizing surveillance and intervention strategies, decision-makers often also need to consider spatially explicit information on other important dimensions, such as the regional specificity of public acceptance, population vulnerability, resource availability, intervention effectiveness, and land use. There is a need for a unified strategy for supporting public health decision making that integrates available data for assessing spatially explicit disease risk, with other criteria, to implement effective prevention and control strategies. Multi-criteria decision analysis (MCDA) is a decision support tool that allows for the consideration of diverse quantitative and qualitative criteria using both data-driven and qualitative indicators for evaluating alternative strategies with transparency and stakeholder participation. Here we propose a MCDA-based approach to the development of geospatial models and spatially explicit decision support tools for the management of vector-borne diseases. We describe the conceptual framework that MCDA offers as well as technical considerations, approaches to implementation and expected outcomes. We conclude that MCDA is a powerful tool that offers tremendous potential for use in public health decision-making in general and vector-borne disease management in particular.

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BackgroundZoonoses are a growing international threat interacting at the human-animal-environment interface and call for transdisciplinary and multi-sectoral approaches in order to achieve effective disease management. The recent emergence of Lyme disease in Quebec, Canada is a good example of a complex health issue for which the public health sector must find protective interventions. Traditional preventive and control interventions can have important environmental, social and economic impacts and as a result, decision-making requires a systems approach capable of integrating these multiple aspects of interventions. This paper presents the results from a study of a multi-criteria decision analysis (MCDA) approach for the management of Lyme disease in Quebec, Canada. MCDA methods allow a comparison of interventions or alternatives based on multiple criteria.MethodsMCDA models were developed to assess various prevention and control decision criteria pertinent to a comprehensive management of Lyme disease: a first model was developed for surveillance interventions and a second was developed for control interventions. Multi-criteria analyses were conducted under two epidemiological scenarios: a disease emergence scenario and an epidemic scenario.ResultsIn general, we observed a good level of agreement between stakeholders. For the surveillance model, the three preferred interventions were: active surveillance of vectors by flagging or dragging, active surveillance of vectors by trapping of small rodents and passive surveillance of vectors of human origin. For the control interventions model, basic preventive communications, human vaccination and small scale landscaping were the three preferred interventions. Scenarios were found to only have a small effect on the group ranking of interventions in the control model.ConclusionsMCDA was used to structure key decision criteria and capture the complexity of Lyme disease management. This facilitated the identification of gaps in the scientific literature and enabled a clear identification of complementary interventions that could be used to improve the relevance and acceptability of proposed prevention and control strategy. Overall, MCDA presents itself as an interesting systematic approach for public health planning and zoonoses management with a “One Health” perspective.

BackgroundLyme disease (LD) is a vector-borne disease that is endemic in many temperate countries, including Switzerland, and is currently emerging in Canada. This study compares the importance of knowledge, exposure and risk perception for the adoption of individual preventive measures, within and between two different populations, one that has been living in a LD endemic region for several decades, the Neuchâtel canton in Switzerland, and another where the disease is currently emerging, the Montérégie region in the province of Québec, Canada.MethodsA web-based survey was carried out in both study regions (814 respondents) in 2012. Comparative analysis of the levels of adoption of individual preventive measures was performed and multivariable logistic regression analyses were used to test and compare how knowledge, exposure and risk perception were associated with the adoption of selected measures in both regions and globally.ResultsIn Montérégie, the proportion of reported adoption of five of the most commonly recommended preventive measures varied from 6% for ‘applying acaricides on one’s property’ to 49% for ‘wearing protective clothing’, and in Neuchâtel, proportions ranged from 6% (acaricides) to 77% for ‘checking for ticks (tick check)’. Differences were found within gender, age groups and exposure status in both regions. The perceived efficacy of a given measure was the strongest factor associated with the adoption of three specific preventive behaviors for both regions: tick check, protective clothing and tick repellent. Risk perception and a high level of knowledge about LD were also significantly associated with some of these specific behaviors, but varied by region.ConclusionsThese results strongly suggest that social and contextual factors such as the epidemiological status of a region are important considerations to take into account when designing effective prevention campaigns for Lyme disease. It furthermore underlines the importance for public health authorities to better understand and monitor these factors in targeted populations in order to be able to implement preventive programs that are well adapted to a population and the epidemiological contexts therein.Electronic supplementary materialThe online version of this article (doi:10.1186/s12889-015-1539-2) contains supplementary material, which is available to authorized users.

Data from wildlife disease surveillance programs are used to inform implementation of disease control (e.g., vaccination, population reduction) in space and time. We developed an approach to increase detection of raccoon rabies in raccoons (Procyon lotor) and skunks (Mephitis mephitis) of Québec, Canada, and we examined the implications of using this approach for targeted surveillance. First we modeled the probability of sampling a rabid animal relative to environmental characteristics of sampling locations. Rabid animals were more likely to be found in low-lying flat landscapes that had higher proportions of corn-forest edge habitat and hay agriculture, and that were within 20 km of one or more known rabies cases. From the model, we created 2 complementary risk maps to identify areas where rabid animals were most likely to be sampled. One map accounted for habitat and known rabies case locations, and can be used to define an infection zone from which surveillance can be targeted along the periphery to determine if disease is continuing to spread. The other map only accounted for habitat and can be used to locate areas most likely to contain rabid animals when the disease is present. In a further analysis we compared the 2 most successful methods for detecting raccoon rabies in Québec, given the disease was present. Government trapping operations (active surveillance) detected more cases in the short-term, but citizen notification (passive and enhanced) was more effective after 12 trapping days from which the initial rabies case was found. Our approach can benefit wildlife and public health agencies wanting to assess the disease status of regions by targeting surveillance to habitats most likely to contain infected animals and by defining the duration over which sampling methods are effective. ß 2011 The Wildlife Society.